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Modelling and forecasting crude oil price volatility with climate policy uncertainty

Author

Listed:
  • Mengxi He

    (Nanjing University of Science and Technology)

  • Yaojie Zhang

    (Nanjing University of Science and Technology)

  • Yudong Wang

    (Nanjing University of Science and Technology)

  • Danyan Wen

    (Nanjing University of Science and Technology)

Abstract

The impact of climate risk on economic and financial fields has attracted considerable interest from academics and practitioners. Recent literature documents that climate risk can affect oil volatility through the dual channel of economic activities and financial markets. Inspired by this, this paper uses climate policy uncertainty (CPU) to examine the predictability of crude oil price volatility. The empirical results indicate that changes in the CPU, rather than the original CPU, can forecast oil volatility. The revealed volatility predictability is both in-sample and out-of-sample. Asset allocation exercise shows that this finding is also economically significant. Furthermore, the predictive ability is mainly concentrated during economic expansions and the CPU contains climate risk that is not available for other predictors. Finally, CPU change indicators can explain the changes in crude oil consumption, which is the economic source of their predictive power.

Suggested Citation

  • Mengxi He & Yaojie Zhang & Yudong Wang & Danyan Wen, 2024. "Modelling and forecasting crude oil price volatility with climate policy uncertainty," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03561-w
    DOI: 10.1057/s41599-024-03561-w
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